[FEAT][Implement MCP into agent.py] #819
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Added necessary modules and Nix configuration for the project's Repl.it environment. The `.replit` file now includes `python-3.10`, `bash`, and Nix channel configuration. Replit-Commit-Author: Assistant
- Enhanced `math_server.py` to handle invalid tool requests and unknown inputs gracefully - Updated `test_integration.py` to include edge case scenarios for validation - Ensured agents dynamically discover available tools and respond accordingly
…server coordination
- Added a log capturing warnings and errors during a multi-agent test run - Includes issues related to API key authentication and LiteLLM model selection
- Fixed configuration issues in `math_server.py` - Integrated API key handling for secure server access
- Modified `test_integration.py` to dynamically use either Swarms or OpenAI key - Enables flexible backend switching for agent API calls
- Included log file capturing multi-agent interactions for financial analysis - Documents system behavior and response patterns during testing
- Improved output formatting in `test_integration.py` for clarity - Updated `math_server.py` configuration for consistent runtime behavior
- Updated input handling to display math calculation results properly - Added log file documenting the fix for future reference
- Fixed server and agent configuration in `math_server.py` and `test_integration.py` - Improved response flow when user input is missing or malformed
- Updated `math_server.py` and `test_integration.py` to explicitly use 'gpt-4o-mini' - Ensures consistent model configuration across test and runtime environments
- Created proper MCP-compatible `math_server.py` - Set up `test_integration.py` with multi-agent system structure - Updated `.replit` config for seamless client-server testing
- Added `README.md` outlining how MCP integration was achieved - Includes details to communicate implementation decisions and task fulfillment
…rage - Improved `math_server.py` and `test_integration.py` for stability - Added structured error handling across MCP components - Aligned implementation with Kye’s task requirements for Swarms MCP integration
- Created `multi_server_test.py` to test coordination across agents and servers - Added `calc_server.py` for handling computation requests - Referenced swarms-rs Rust architecture for Python-based design structure
…lient.py and mock_math_server.py
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…structure.txt, .replit, attached_assets)
…1729/swarms into feature/mcp-integration
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Pull Request Description:
Description:
This PR finalizes and stabilizes full MCP (Model Context Protocol) integration into the Swarms multi-agent architecture. It includes the following major improvements:
MCP Server Enhancements:
mcp_client.pyandmcp_server.pyto useFastMCPwith correct async and port configurationsAgent & Client Improvements:
agent.pyto support parallel task execution and prevent duplicate tool callsMCPServerSseParamsinitialization and agent response formattingTesting & Workflow:
pytestOutput & Logging:
Documentation:
Issue:
N/A — this is the initial stable release of full MCP multi-agent integration.
Dependencies:
fastmcp,langchain-openai,LiteLLM,anyioTag maintainer:
@kyegomez
Twitter handle:
https://twitter.com/the_complex_one